State Command Center
Decisions, not dashboards · what to act on now
records
Priority action queueact now · ranked by severity
Synthesising command picture
State threat boarddistrict trajectory
District30dTrendClear%Level
Proactive deployment forecastresponsible · evidence-based · not a black box
Official Crime Review
Published totals · National Crime Records Bureau & Karnataka State Police · real, citable figures
Bengaluru City — crimes by head (2023)cases registered
Crime headCases 2023Source
Karnataka State (2023)statewide
12-month crime trend
Case lifecycle
Pipeline from registered FIR → court → disposal. Resolution = solved + closed as a share of all cases.
Crime type composition
Clearance rate by districtsolved ÷ total
Incident map · all districts
All months
Active hotspot
Normal district
click any dot for detail · drag the slider to play months
About locations: the illustrative sample cases are placed approximately (area-level, not the true spot — record-level locations are confidential). FIRs registered in this console are pinned at the exact spot the officer marks on the form's map.
District workload
DistrictCasesOpenClear%
Police station performancetop 10 by workload
StationTotalOpenClearedClearance
City Commissionerates6 · city police
Police Ranges7 · district police
Repeat-offender watchlist
#OffenderRolePrimary MOCasesLast activeRisk priority
Risk = investigation priority, not a prediction. Score (0–100) is itemised from qualifying case count, recency, repeated vehicle-borne MO, and links to known associates. An officer decides — the system only ranks and shows its working.
Link analysis
Hub Key connector Ring member Co-accused Associate
Network read-outwho matters & why
Mapping links
How to read this: each dot is a person; lines join people accused together or known to associate. The hub is the most-connected offender; a key connector holds two sub-groups together — removing one splits the network apart. Hover any dot to isolate its links. Built only from real case records — nothing inferred.
Computing MO fingerprints
Incidents by weekdaypatrol planning
Seasonal & event lenscalendar patterns · expectation-weighted
Recent case registerlatest 12 FIRs
Case No.TypeDateStationStatus
Register a new FIRvalidated entry · feeds analytics live
Local police file the case here. It is validated server-side (recognised crime types & districts, no future dates, FIR-number format) and immediately joins the live analytics — one source of truth, no separate data entry. Write access is limited to Station Officer, Investigator and Supervisor roles; every registration is audited.
Import case dataCCTNS / SCRB export · check first, then confirm
↓ CSV template ↓ CCTNS export sample Rows are checked first — nothing is written until you confirm.
The real-world intake path. Every FIR in Karnataka is already digital (CCTNS); SCRB can export it as a spreadsheet. Upload that export here — every row passes the same validation rulebook as a hand-registered FIR (recognised types & districts, station names normalised, no future dates, no duplicates), you review the result, then confirm the write. Rejected rows are listed with the reason and line number — fix and re-upload just those. Access: District Command (own district only) and SCRB Analyst (statewide). Every import is audited.
Social context · real public data, cited
Why crime clusters here — driversreal socio figure × this area’s real crime share
How criminologists read thisthe five lenses, in plain words
Who is involvedvictims & accused · age / gender, FIR-recorded
Who is being targeted — community impactaggregate only · complainant-reported · never individual profiling
Authorised feed connectorsplug-in ready · not live in this demo
Corroboration laddershow a lead's confidence rises as feeds are added
The evidence ladderrecord → identity → device/biometric → officer-confirmed
What this preventsthe mistakes corroboration stops
Sample case ↓ CSV template Analysed in your browser + in-memory — not stored.
Money-flow traildeposits → mules → collectors → controller → cash-out
Money-flow tracesa deposit followed hop-by-hop to cash-out · real refs
Priority — investigate these accounts firstcontrollers → collectors → high-risk mules
Laundering ringsconnected sub-networks moving money together
Traced cash-out by ring
Deposits by betting app
Telegram recruitmentmule-account onboarding
Betting-app account rotationmerchant → rotating beneficiary accounts
Betting merchantMule accounts usedDepositsTxns
Illustrative sample · the same engine runs on real bank STR / UPI feeds. Accounts pseudonymised · leads, not verdicts.
Ask — English or ಕನ್ನಡgrounded · evidence-backed · voice
Type, or tap the mic to speak
Evidence · grounded records
Every number here is worked out live from the real case database — nothing is estimated or made up.